Where we explore the career stories & experiences of some of the most successful people in the field of Data and Analytics.
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June 9, 202652 min
Season 6 - Episode 5 - "The Insurance Nobody Wants: Why Data Governance Matters Now" with Belinda Toniolo
Data governance has stopped being about rules and started being about survival. In this episode, Belinda walks through how her team shifted from gatekeeper to guide pairing technical and business minds, educating instead of enforcing, and learning to say no to perfection. We talk about what actually works when you're moving at speed, how AI forced organisations to finally care about data quality and the honest part nobody mentions: what it feels like to be seen as the insurance policy nobody wants to buy.
May 25, 202642 min
Season 6 - Episode 4 “Build, Ship, Improve” - The Commercial Mindset Behind AI That Reaches Real Customers" with Tracy Moore
In this episode, I sit down with Tracy Moore, GM of AI and Data at MYOB, for one of the most refreshingly honest conversations I've had about what it takes to build AI products that reach real customers. Tracy and her team have been quietly doing the hard work of shipping AI to millions of small businesses across Australia and New Zealand and the lessons they've learned along the way are ones every data and AI leader needs to hear.We talk about why most AI initiatives stall before they ever get shipped, the difference between exploring and actually building and why having a commercial mindset is the thing that changes everything. Tracy also shares how why treating data and AI as a team sport has been central to their success. If you've ever felt like your organisation is stuck between experimentation and real impact this one is for you.🎧 Listen to the full episode on Spotify or Apple Pod (Links in the comment below)
May 12, 202645 min
Season 6 - Episode 3 - "The one question that changed HR’s influence on business performance forever" with Sarah Novelli
HR doesn’t lose influence because it lacks insight.It loses influence because it talks in the wrong language.In this episode of Lead With Data, we speak to a senior business executive who didn’t come from a data background like our usual guests but fundamentally changed her seat at the table by doing one thing differently: connecting workforce data directly to revenue, margin and productivity.No dashboards for show. Just data translated into decisions executives actually care about.This conversation shows what happens when people metrics stop being “HR numbers” and start being business performance indicators.If you work in HR, people and culture or any function that wants to influence outcomes, not just report activity, this one is worth your time.Key takeawaysPeople data is business performance data, not HR reportingVacancies aren’t an HR problem, they’re delayed revenueIf you can’t link initiatives to margin or productivity, they won’t get tractionInfluence comes from translation, not more dashboards
April 27, 202646 min
Season 6 - Episode 2 - “Why data and AI teams need translators not just tools” with Clare Kitching
Why Data Teams Need Translators, Not Just ToolsIn this episode of Lead With Data, Rina Gami sits down with Clare Kitching, a senior data leader who works closely with organisations navigating complex data and AI decisions. The conversation explores why many data and AI initiatives stall and not because of tooling gaps.The conversation unpacks how data teams are navigating generative AI, agentic AI and increasing pressure to move quickly, often without the shared language, context and alignment required to succeed. Clare shares what she is seeing first-hand across organisations grappling with executive expectations, shadow AI, governance concerns and the widening distance between technical teams and business leaders.This episode focuses on the growing importance of translators in data teams' people who can bridge strategy, technology and value and what leaders should be paying attention to before scaling AI.In this episode, we cover:Why tools alone do not solve AI and data challengesThe shift from traditional data initiatives to generative AI and agentic-based AIThe critical role of senior executive sponsorship in AI successHow translators help close the gap between technical teams and the businessPractical ways organisations can start or scale AI responsiblyEvolving roles in data teams, including analytics translators and AI governance specialistsCommon challenges such as shadow AI, data quality and organisational buy-inIndicators that signal true readiness to scale AIWhy value-led AI initiatives matter more than experimentationTimestamps00:00 – AI as a high-return capability in modern data teams01:32 – Claire’s career journey and move into consulting03:16 – What has changed in data and AI over the last five years04:00 – Where organisations are really at in their AI journeys05:24 – Pressure to move quickly and what gets missed06:03 – Executive sponsorship and its impact on outcomes07:30 – Data team structures and emerging gaps08:53 – Organisational barriers to AI adoption10:38 – Shadow AI and responsible use12:34 – Initial assessment points when working with organisations14:47 – Asking the right questions to align AI to value17:11 – Why communication is now a core data capability19:09 – Telling the data story in a way the business understands22:18 – Structuring data teams for sustainable AI outcomes25:26 – Evolving roles across data, engineering and governance28:11 – Everyday AI, generative AI and agent AI explained32:21 – Leadership priorities when advancing AI initiatives33:49 – Signs an organisation is ready to scale AI responsibly35:11 – Maintaining momentum without creating risk36:08 – Hiring for AI capability beyond technical skills38:25 – When and why to involve external expertise41:17 – The value of an external perspective44:48 – Avoiding stagnation in AI programs45:27 – Communication and storytelling as critical capabilities46:16 – Leadership alignment and organisational readiness46:44 – Final reflections and next stepsResources & LinksExperian Data Studio – supporting stronger data governance and trustClaire Kitching Linkedin Website - cambiq.com.au
April 13, 202639 min
Season 6 - Episode 1 - Why "fail fast" is a powerful mindset if you want to succeed in Data Innovation
In this episode, Nick Jameson shares his journey from aerospace engineering and defence to data leadership. He discusses why the fail fast mindset is important for Data Innovation, how high-stakes environments influence building resilient data platforms, the importance of problem-solving, stakeholder engagement and managing technical debt. Gain insights into effective leadership, balancing innovation with foundational stability and the future of data engineering and analytics.Data Engineering, Data Leadership, High-Stakes Environments, Data Platforms, Analytics, Tech Debt, Leadership, AI, Data StrategyKey topics:Transferable skills from aerospace to dataBuilding resilient and scalable data platformsManaging technical debt and platform maturityLeadership principles in data teamsThe impact of AI and emerging technologiesChapters00:00 Embracing Opportunities and Learning from Failure02:50 Transitioning from Aerospace to Data Analytics05:58 Core Principles from High-Stakes Engineering08:33 Decision-Making Under Pressure11:41 Balancing Processes and Flexibility in Data Analytics14:36 Managing Expectations and Prioritization17:16 Building Robust Data Platforms for Future Challenges20:04 The Interplay of Data Engineering and Advanced Analytics22:25 Building Robust Data Pipelines23:23 The Risks of Premature Analytics25:46 Challenging Assumptions in Data Teams27:16 Balancing Investments in Data Tools28:43 Leadership Lessons from Engineering31:03 Managing Stress in Leadership34:38 Advice for Nonlinear Moves into Data36:07 Building a Modern Data Platform38:26 Investing in People as a Leader40:15 The Future of Data Engineering and AnalyticsResourcesExperian Data SolutionsNick Jameson on LinkedIn
December 2, 202542 min
Episode 20 - AI at the tipping point: Governance, Trust and ROI
As we wrap up the final episode of Season 5 of the Lead with Data podcast, we explore why so many AI pilots fail. Joining me is Noel Hanssens, and together we unpack the biggest challenges organisations face when implementing AI, including governance gaps, misconceptions and misalignment with strategy. We also discuss the need for AI literacy across teams and the critical role of CFOs in guiding AI investments. Packed with real-world insights, this episode highlights how to unlock AI’s potential while keeping implementation responsible and strategic.
November 18, 202543 min
Episode 19 - The Data You Don’t Control Controls You with Pushkar Mishra
Joining me in this week’s episode is Pushkar Mishra, who brings sharp insights into the powerful connection between data risk, governance and organisational transformation. Pushkar shares why neglecting data quality can be costly, how engaging stakeholders effectively can showcase the true business value of data governance and the pivotal role data champions play in driving change. We also dive into the ethical implications of AI and the emerging risks shaping the future of data management. This episode is packed with actionable insights for leaders looking to turn data governance into a strategic advantage that fuels growth and innovation.Key topics we discuss include:The Interconnection of Transformation and Data RiskChallenges in Perception of Data GovernanceThe Cost of Ignoring Data GovernanceExecution Challenges in Data Governance StrategiesUnderstanding Business Value in Data GovernanceFuture Data Risks and Ethical Considerations
November 4, 202542 min
Episode 18 - The Truth About Technical Debt That No One Talks About with Mark Sergeant
Joining me in this week’s episode is Mark Sergeant he offers a candid perspective on why managing technical debt requires more than quick fixes; it demands strategic thinking and collaboration.Our conversation dives into:- Measuring and managing technical debt effectively- Building transparency between data teams and business leaders- Adopting a thoughtful approach to modernisationMark also shares practical advice on tackling visible pain points first and ensuring data initiatives deliver consistent, long-term value. For data and technology leaders, this episode provides actionable insights to balance innovation with sustainability and drive meaningful business outcomes.
October 22, 202547 min
Episode 17 - The Real Reason You Can’t Keep Data Talent
In this episode, I sit down with Lucas Dahan to unravel the complexities of building and retaining effective data teams. We tackle the challenges of high staff turnover and explore how shifting from a support to a product mindset can transform team dynamics. Lucas shares his insights from working across different sizes of organisations, from scale-ups to large corporates, emphasising that no matter how big or small, you can still transform your teams. Join us for a conversation that might just get you to rethink and reshape your approach to running your data teams.Key Topics:The Structure and Challenges of Data TeamsThe Shift from Support to Product TeamsImplementing Change in Large OrganizationsTransforming Engineering MindsetsShifting from Reporting to Problem SolvingFostering Ownership and AccountabilityManaging Diverse Skill SetsEmpowering Team Members for Ownership
October 7, 202552 min
Episode 16 - Unlocking Business Value with Data Governance with Martin Soley
In this episode of the Lead with Data podcast, I sit down with Martin Soley to talk data governance and unlocking business value. We discuss the complexities and challenges organisations face, the importance of aligning governance with business strategy and the evolving role of data governance leaders. Martin shares insights on the importance of engaging with business owners and where using technology can improve data quality. The conversation highlights the need to understand business drivers to show the value of data governance and why you can’t afford not to do this.Key TakeawaysData governance can often feel like a box-ticking exerciseOrganisations face various challenges in data quality and governanceCommon mistakes include lack of buy-in and misalignment with business goalsData governance should be part of the business cultureEffective governance is about turning data into actionable knowledgeEngaging with business owners is crucial for data insightsTechnology can help automate data quality processesCommunication skills are essential for governance leadersThe future of data governance will require more business literacy
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